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Record W4411001923 · doi:10.3917/rfeap.016.0098

De l’attestation au dialogue. Dispositifs mis en œuvre pour se comprendre et contribuer à une démocratie en santé

2025· article· fr· W4411001923 on OpenAlexaff
Bruno Hubert, Martine Janner-Raimondi, Valérie Viné Vallin, Julia Midelet

Bibliographic record

VenueRevue française d éthique appliquée · 2025
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPolitical sciencePhilosophyHumanities

Abstract

fetched live from OpenAlex

Este artículo analiza cómo el movimiento de los chalecos amarillos se constituyó como un contrapúblico en línea, utilizando como caso de estudio su reacción a la cobertura mediática que recibió. Para comprender las fuerzas motrices de este proceso, la investigación que aquí se presenta se basa en un trabajo de campo que combina la observación de los espacios de Facebook relacionados con el movimiento y entrevistas semiestructuradas. En primer lugar, el análisis muestra que las publicaciones difundidas en línea mantuvieron una continuidad con la experiencia de las movilizaciones, tanto en lo que se refiere a la narración de los acontecimientos como a las emociones vividas. A esta capacidad de resonancia de las experiencias de los activistas se añade la construcción de un marco que identifica a los adversarios del movimiento, basado en un sentido compartido de la justicia y en la denuncia del funcionamiento de los medios de comunicación dominantes. Este estudio documenta la coalición de militantes en torno a una experiencia compartida que sirve de base para la construcción de un discurso político.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.036
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.057
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0160.036
Scholarly communication0.0250.022
Open science0.0020.013
Research integrity0.0150.017
Insufficient payload (model declined to judge)0.0250.007

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.400
Teacher spread0.368 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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